Three Years of the Lightning Imaging Sensor Onboard the International Space Station: Expanded Global Coverage and Enhanced Applications

Blakeslee, Richard J.; Lang, Timothy J.; Koshak, William J.; Buechler, Dennis E.; Gatlin, Patrick; Mach, Douglas M.; Stano, Geoffrey T.; Virts, Katrina S.; Walker, T. D.; Cecil, Daniel J.; Ellett, Will; Goodman, Steven J.; Harrison, Sherry; Hawkins, Donald Lamar; Heumesser, Matthias; Lin, Hong; Maskey, Manil; Schultz, Christopher J.; Stewart, M. F.; Bateman, Monte; Chanrion, Olivier; Christian, H. J.

doi:10.1029/2020jd032918

Cited by 93 publications

(131 citation statements)

References 67 publications

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“…Note that all three systems show a lack of lightning data over the ocean to the west of South America. This lack of lightning has been seen in other studies with different lightning sensors, e.g., Albrecht et al (2016), Blakeslee et al (2020). To keep the DE and FAR statistics from having too much variation, we will not plot DE and FAR values when the number of flashes per grid point drops below 20 flashes for either the GLMs or the virtual ground truth source.…”

Section: Accepted Articlementioning

confidence: 93%

Further Investigation Into Detection Efficiency and False Alarm Rate for the Geostationary Lightning Mappers Aboard GOES‐16 and GOES‐17

Bateman

Mach

Stock

2021

Earth and Space Science

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The Geostationary Lightning Mapper (GLM) is a geostationary lightning detection and location instrument, developed for the R generation of Geostationary Operational Environmental Satellites (GOES‐R, S, T, and U). This paper details a new technique to assess detection efficiency (DE) and false alarm rate (FAR), which indicate how well the instrument is detecting lightning and rejecting nonlightning. In an attempt to compare GLM with the best possible ground truth data, we clustered several ground‐based lightning networks into a single “virtual” network and compare it to the GLM results. A major issue with determining the GLM DE and FAR values is that over much of the instrument field of view (FOV), there are no high DE systems. To assess the GLM DE and FAR over these regions, we modified our prior coincidence criteria by increasing the time window from ±1 s to as much as ±10 min to account for the lower DE of the ground truth systems. Using the expanded time window, we compare GLM flash data from August 1, 2019 through January 31, 2020 for both instruments against the virtual network lightning flash data. We find that increasing the time window, while maintaining the distance criteria of 50 km, greatly improve the DE and FAR values. With the full ±10 min time window, over the whole GLM FOV, the GLMs on GOES‐16 and GOES‐17 have a DE of over 90%. For the same time window, the FAR for GLM on GOES‐16 is just over 5%, while the FAR for the GLM on GOES‐17 is just under 20%.

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Section: Accepted Articlementioning

confidence: 93%

Further Investigation Into Detection Efficiency and False Alarm Rate for the Geostationary Lightning Mappers Aboard GOES‐16 and GOES‐17

Bateman

Mach

Stock

2021

Earth and Space Science

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“…Pixelated lightning imagers including the Optical Transient Detector (OTD; Boccippio et al, 2000), Lightning Imaging Sensor (LIS; Blakeslee et al, 2020;Christian et al, 2000), Geostationary Lightning Mapper (GLM; Goodman et al, 2013;Rudlosky et al, 2018), and Lightning Mapping Imager (LMI; Yang et al, 2017) record the spatial distributions of optical energy that result from lightning pulses. These observed spatial radiance patterns often deviate from the simple idealized model of radiance decreasing only with radius from the center pixel.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Transmission of Optical Lightning Signals Through Complex 3‐D Cloud Scenes

Peterson

2020

JGR Atmospheres

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Space-based lightning imagers have shown that complex cloud scenes consisting of multiple tall convective features, anvil clouds, and warm boundary cloud layers are illuminated by lightning in many different ways depending on where the lightning occurs and how energetic it is. Modifications to the optical lightning signals from radiative transfer in the cloud medium can lead to reductions in detection efficiency and location accuracy for these instruments and can also cause some of the optical signals that are detected to have unexpected spatial energy distributions. In this study, we perform Monte Carlo radiative transfer simulations of optical lightning emissions in clouds with complex 3-D geometries to shed some light on the origins of certain irregular radiance patterns that have been recorded from orbit. We show that diffuse reflections off nearby cloud faces can explain lightning signals in nonelectrified clouds, tall clouds can result in poor optical transmission and suppressed radiances that could lead to missed events and that particularly favorable viewing conditions can cause otherwise normal lightning to produce a superbolt that is orders of magnitude brighter than the same flash seen from a different angle. Plain Language Summary Lightning is detected from space using instruments that report rapid changes in cloud brightness from lightning illumination. However, this light can be modified by scattering and absorption in the cloud. Scattering off water drops causes portions of the signal to be diluted in space and delayed in time. What starts off as an impulsive point light source in the cloud may illuminate a region of the cloud-top that is 100 km across with a waveform that persists over significant fraction of a millisecond. Interactions between the optical lightning emissions and the cloud scene are particularly complex when the surrounding clouds do not take on a simple geometric shape. Clouds observed in nature often contain multiple vertical layers including warm boundary clouds and overhanging anvils. Understanding some of the more irregular spatial energy distributions recorded by space-based lightning sensors requires accounting for these complex geometries. In this study, we develop 3-D cloud models that approximate cloud structures found in nature and perform Monte Carlo radiative transfer simulations of how they are illuminated by lightning. In doing so, we confirm the suspected origins of irregular cloud illumination, such as reflections off of nearby cloud faces or particularly favorable viewing conditions allowing normal lightning to appear highly energetic.

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“…There were 285 ISS LIS flashes matched to lightning identified from METEOR camera frames, which is a relative DE of 92%. Blakeslee et al [2020] observed that ISS LIS relative DE ranged from 51% to 75% when compared to other lightning observing systems, and the higher DE obtained here again is likely in part due to nighttime, the optical nature of METEOR, and the large average flash size during this period of time. individual frames (Fig.…”

Section: Flash Population Statistics Using Meteormentioning

confidence: 39%

“…Lightning Imaging Sensor (LIS) was launched and made operational on the International Space Station [ISS; Blakeslee and Koshak, 2016;Blakeslee et al, 2020]. This instrument has heritage back to the Tropical Rainfall Measurement Mission [TRMM; Kummerow et al, 1998] LIS [Christian et al, 2000;Boccippio et al, 2001] instrument, where ISS LIS was the spare backup in the event the LIS instrument on TRMM failed during preparation and launch.…”

Section: Accepted Articlementioning

confidence: 99%

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A Technique for Automated Detection of Lightning in Images and Video From the International Space Station for Scientific Understanding and Validation

Schultz

Lang

Leake

et al. 2021

Earth and Space Science

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A combination of Chiba University's METEOR camera, International Space Station Lightning Imaging Sensor (ISS LIS), Geostationary Lightning Mapper (GLM), National Lightning Detection Network (NLDN) data, and other space and ground based data sets were utilized to develop a METEOR‐derived lightning identification technique to automatically identify lightning flashes within International Space Station video and still frame imagery. Approximately 14,000 frames were used from two METEOR camera videos. Zero lightning events were missed by the technique using manual inspection of both videos, and the technique did not identify other sources of light (e.g., city lights). Three‐hundred and nine METEOR‐identified flashes were matched with 289 GLM flashes and 285 ISS LIS flashes in the METEOR field of view on May 17, 2017. On average, the flash area determined by the analysis technique developed in this study was 266 km2 smaller than the flash area observed by GLM. The primary reason for this difference in size was the spatial resolution of GLM and METEOR (>8 km vs. 260 m). When NLDN flashes were observed, there was a 200–500 km2 increase in the algorithm‐derived flash area within 100 ms of the NLDN time, indicative of return stroke processes as bright light is scattered through cloud top. Accurate reverse geolocation using lightning data alone was difficult due to the different spatial resolution, temporal resolution, and other geolocation assumptions between the camera images and comparison data. However, the use of satellite‐derived city lights aided in the geolocation process for scientific comparisons.

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Three Years of the Lightning Imaging Sensor Onboard the International Space Station: Expanded Global Coverage and Enhanced Applications

Cited by 93 publications

References 67 publications

Further Investigation Into Detection Efficiency and False Alarm Rate for the Geostationary Lightning Mappers Aboard GOES‐16 and GOES‐17

Further Investigation Into Detection Efficiency and False Alarm Rate for the Geostationary Lightning Mappers Aboard GOES‐16 and GOES‐17

Modeling the Transmission of Optical Lightning Signals Through Complex 3‐D Cloud Scenes

A Technique for Automated Detection of Lightning in Images and Video From the International Space Station for Scientific Understanding and Validation

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